Clustering as an EDA method: the case of pedestrian directional flow behavior.
Vol 3 No 1 (2010)

Clustering as an EDA method: the case of pedestrian directional flow behavior.

Research Article
https://doi.org/10.21500/20112084.820
Published June 30, 2010
Kardi Teknomo
Ateneo de Manila University
Ma. Regina E. Estuar
Ateneo de Manila University
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Keywords

Gaussian Mixture
directional flow pattern
pedestrian behavior
trajectory analysis

How to Cite

Teknomo, K., & E. Estuar, M. R. (2010). Clustering as an EDA method: the case of pedestrian directional flow behavior. International Journal of Psychological Research, 3(1), 23-36. https://doi.org/10.21500/20112084.820
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Abstract

Given the data of pedestrian trajectories in NTXY format, three clustering methods of K Means, Expectation Maximization (EM) and Affinity Propagation were utilized as Exploratory Data Analysis to find the pattern of pedestrian directional flow behavior. The analysis begins without a prior notion regarding the structure of the pattern and it consequentially infers the structure of directional flow pattern. Significant similarities in patterns for both individual and instantaneous walking angles based on EDA method are reported and explained in case studies.
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References

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